CN115953696A - Method and device for precision quality inspection of stereoscopic satellite image and electronic equipment - Google Patents
Method and device for precision quality inspection of stereoscopic satellite image and electronic equipment Download PDFInfo
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Abstract
The application provides a method, a device and electronic equipment for precision quality inspection of stereoscopic satellite images, which relate to the technical field of photogrammetry and remote sensing, and the method comprises the following steps: acquiring a stereopair in the same measurement area of the stereoscopic satellite image, and constructing an image pyramid corresponding to the stereopair; step-by-step matching is carried out on the image pyramid based on a preset search radius, and homonymous pixel points corresponding to the reference image in the stereoscopic image pair are determined; carrying out space forward intersection processing on the pixels with the same name to obtain object space coordinates corresponding to the stereo pair; and determining precision data among the stereo satellite images based on the object space coordinates, and performing precision quality inspection based on the precision data. The method and the device can automatically eliminate wrong connection points, and simultaneously introduce multiple control points for synchronously checking absolute accuracy.
Description
Technical Field
The application relates to the technical field of photogrammetry and remote sensing, in particular to a method and a device for precision quality inspection of a stereoscopic satellite image and electronic equipment.
Background
At present, in the conventional technology, although the stereo model edge matching precision is checked by using a connection point when performing photogrammetry, the method of using artificial pricking points is troublesome and labor-consuming when extracting the same-name points, and the result is excessively dependent on the artificial pricking point precision. When the automatic matching connection point method is used, error points are matched most possibly under the conditions of poor texture quality and the like.
Disclosure of Invention
The application aims to provide a method, a device and electronic equipment for precision quality inspection of stereoscopic satellite images, which can automatically eliminate wrong connection points and simultaneously introduce multiple control points for synchronously inspecting absolute precision.
In a first aspect, the present invention provides a method for precision quality inspection of a stereo satellite image, the method comprising:
acquiring a stereopair in the same measurement area of the stereoscopic satellite image, and constructing an image pyramid corresponding to the stereopair;
step-by-step matching is carried out on the image pyramid based on a preset search radius, and homonymous pixel points corresponding to the reference image in the stereoscopic image pair are determined;
carrying out space forward intersection processing on the homonymous pixel points to obtain object space coordinates corresponding to the stereopair;
and determining precision data among the stereo satellite images based on the object space coordinates, and performing precision quality inspection based on the precision data.
In an alternative embodiment, the image pyramid includes image data of at least two levels of resolution; matching the image pyramid step by step based on a preset search radius, and determining the homonymous pixel points corresponding to the reference image in the stereoscopic image pair, wherein the method comprises the following steps:
extracting the maximum gray gradient point position in a local window from the stereo image pair, and determining the maximum gray gradient point position as a feature point to be matched;
taking the feature point to be matched as a center, and reading an image data block to be matched based on a preset matching template;
and matching step by step in the image pyramid according to the position relation between the stereoscopic image pair and the reference image and a preset search radius, and determining the homonymous pixel points corresponding to the stereoscopic image pair and the reference image.
In an optional embodiment, the step-by-step matching is performed in the image pyramid according to the position relationship between the stereo image pair and the reference image and a preset search radius, and determining the homonymous pixel point corresponding to the reference image in the stereo image pair includes:
determining a search area in the reference image according to the position relation between the stereo pair and the reference image;
performing window sliding on the image pyramid in the search area based on a preset search radius, performing step-by-step matching in the sliding process, and calculating a correlation coefficient between the feature point to be matched and the matched target connection point; the size of the preset matching template is smaller than that of the preset search radius;
and determining the homonymous pixel points corresponding to the reference image in the stereoscopic image pair based on the correlation coefficient.
In an optional embodiment, performing window sliding in the image pyramid based on a preset search radius in the search area, performing progressive matching in the sliding process, and calculating a correlation coefficient between the feature point to be matched and the matched target connection point, includes:
performing window sliding on a preset initial layer of the image pyramid in the search area based on a preset search radius;
when the window slides, if the target connection point is matched, performing matching search on the next layer of a preset initial layer based on the position of the target connection point; if the target connection point is not matched, increasing the value of the preset search radius, performing matching search on a preset initial layer through the increased search radius, and performing matching search on the next layer of the preset initial layer based on the position of the target connection point after the target connection point is matched; the resolution of the next layer of the preset initial layer is greater than that of the preset initial layer;
and performing step-by-step circular matching search on the image pyramid until the image pyramid is circulated to the end layer of the image pyramid, and calculating the correlation coefficient between the feature point to be matched and the target connection point matched in the end layer.
In an alternative embodiment, the method further comprises:
when step-by-step matching search is carried out, the matched target connection point is processed based on the block level difference model, and a residual vector corresponding to the target connection point after adjustment is obtained;
and determining an error point in the target connection point based on the residual vector and a preset residual threshold value, and eliminating the error point.
In an alternative embodiment, a stereo pair in the same field of view of the stereo satellite image includes a first image and a second image; the homonymous pixel point comprises a first connecting point positioned in the first image and a second connecting point positioned in the second image, and the first connecting point and the second connecting point are homonymous points;
carrying out space forward intersection processing on the homonymous pixel points to obtain object space coordinates corresponding to the stereopair, and the method comprises the following steps:
determining a ground image point of the same-name pixel point intersected on the ground based on the coordinates of the first connecting point and the coordinates of the second connecting point;
and calculating based on the ground image points and the rational function model, and determining the object coordinates corresponding to the stereopair.
In an optional embodiment, performing precision quality inspection based on the precision data includes:
performing precision quality inspection based on the multi-degree control points and/or the error evaluation parameters; and the multi-degree control points are homonymous image points obtained by importing field control points in the stereoscopic image pair or matching the field control points with a standard image superposition digital elevation model.
In a second aspect, the present invention provides an apparatus for precision quality inspection of stereoscopic satellite images, the apparatus comprising:
the image pyramid construction module is used for acquiring a stereopair in the same measurement area of the stereoscopic satellite image and constructing an image pyramid corresponding to the stereopair;
the step-by-step matching module is used for performing step-by-step matching on the image pyramid based on a preset search radius and determining homonymous pixel points corresponding to the reference image in the stereoscopic image pair;
the front intersection processing module is used for carrying out space front intersection processing on the pixel points with the same name to obtain object space coordinates corresponding to the stereo pair;
and the precision quality inspection module is used for determining precision data among the stereo satellite images based on the object space coordinates and performing precision quality inspection based on the precision data.
In a third aspect, the present invention provides an electronic device, including a processor and a memory, where the memory stores computer-executable instructions executable by the processor, and the processor executes the computer-executable instructions to implement the method for precision quality inspection of stereoscopic satellite images according to any one of the foregoing embodiments.
In a fourth aspect, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when invoked and executed by a processor, cause the processor to implement the method for precision quality inspection of stereoscopic satellite images according to any one of the preceding embodiments.
The application provides a method, device and electronic equipment of quality control of stereoscopic satellite image precision, at first acquire the stereoscopic image pair in the same survey district of stereoscopic satellite image, and establish the image pyramid that the stereoscopic image pair corresponds is in based on preset search radius the image pyramid matches step by step, confirms the homonymy pixel that corresponds with the benchmark image in the stereoscopic image pair carries out space place ahead rendezvous and handles, obtains the object side coordinate that the stereoscopic image pair corresponds, based on the precision data between the stereoscopic satellite image is confirmed to the object side coordinate, and based on the precision data carries out the precision quality control. The method can automatically eliminate wrong connection points, and simultaneously introduces a plurality of control points for synchronously checking absolute accuracy.
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In order to more clearly illustrate the detailed description of the present application or the technical solutions in the prior art, the drawings needed to be used in the detailed description of the present application or the prior art description will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative efforts.
Fig. 1 is a flowchart of a method for precision quality inspection of a stereo satellite image according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of an image pyramid according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a search match according to an embodiment of the present application;
fig. 4 is a schematic diagram of a precision quality inspection result according to an embodiment of the present disclosure;
fig. 5 is a structural diagram of an apparatus for precision quality inspection of a stereo satellite image according to an embodiment of the present disclosure;
fig. 6 is a block diagram of an electronic device according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined or explained in subsequent figures.
At present, the research and verification of the positioning accuracy of the resource three-dimensional satellite images utilize the resource three-dimensional satellite image data and orbit parameters to perform relative orientation and absolute orientation on the three-dimensional images, and generate a epipolar line three-dimensional model, and utilize a secret point with the accuracy specification of 1. Through experimental error analysis, the method fully verifies that the resource three-dimensional image data meets the requirement of 1.
The method comprises the following steps of (1) domestic single-line array remote sensing satellite different-orbit stereotactic precision verification: aiming at the verification of the stereotactic precision of domestic high-resolution optical remote sensing agile satellites of remote sensing No. 26 and remote sensing No. 28, a manual selection mode is adopted for research, control points are derived from DOM and DEM of basic geographic information digital result 1: 2 000, the plane precision of a flat land and the plane precision of a mountain land are respectively 1.2 m and 1.6 m, and the elevation precision is respectively 0.5 m and 1.5 m. The control point mainly selects some manually-interpreted ground features such as road intersections, building foot points and the like, and the accuracy of the pricking point is about 1 pixel due to the fuzzy effect at the edge of the image. Experimental verification results show that the three-dimensional adjustment result can obtain plane positioning accuracy better than 1 m and elevation accuracy better than 2 m.
The method for checking the edge connecting precision of the three-dimensional model under the forward intersection principle comprises the following steps: aiming at the problem of automatic detection of the edge connection precision of the three-dimensional model, a three-dimensional model edge connection precision detection method based on front intersection is provided. The method is based on automatic matching or manual thorn judgment to obtain the same-name point, and utilizes the forward intersection technology to obtain the corresponding ground point coordinates, and carries out coordinate conversion and coordinate difference calculation. The article analyzes and evaluates the edge jointing precision through various indexes such as the middle error, the average value and the like of the coordinate difference, and adopts a plurality of groups of actually measured data to carry out experimental verification. Analysis results show that the method can accurately and efficiently detect the edge connection precision condition between the three-dimensional images and can provide good data support for quality evaluation and subsequent data processing analysis of the three-dimensional model.
The field measurement control point has the characteristic of high precision, and the field measurement control point is often used as a precision check point in the prior art. However, the field measurement work has huge manpower and material consumption and no timeliness, and meanwhile, the confidentiality of the field measurement work is considered, so that the method for using the field control point in the precision inspection work is restricted. In addition, although the manual pricking method can avoid field measurement, the efficiency of field pricking is still low, and the precision of the method excessively depends on the precision of manual pricking. The available data shows that the three-dimensional model precision checking method based on automatic matching is less, and the matching error points are not processed.
In the prior art, although the connection point is used for checking the edge connection precision of the three-dimensional model, when the homonymous point is extracted, the method of using the artificial pricking point is troublesome and labor-consuming, and the result is excessively dependent on the accuracy of the artificial pricking point. When the automatic matching connection point method is used, error points are matched most possibly under the conditions of poor texture quality and the like.
Based on this, the embodiment of the application provides a method, a device and an electronic device for precision quality inspection of a stereo satellite image, which can automatically eliminate wrong connection points and simultaneously introduce multiple control points for synchronously inspecting absolute precision.
The embodiment of the application provides a method for precision quality inspection of a stereo satellite image, which is shown in fig. 1 and mainly comprises the following steps:
step S110, obtaining a stereopair in the same measurement area of the stereoscopic satellite image, and constructing an image pyramid corresponding to the stereopair.
The input is a multi-view stereopair with mutual overlapping in the same measuring area, usually the forward-looking and backward-looking data of a stereo satellite image. According to different quality inspection purposes, the input data can be original rpc data or data subjected to regional network adjustment.
The image pyramid is a layer set of a plurality of levels obtained by downsampling original image data, and data with specified resolution can be used through the retrieval pyramid in software application, so that the operation amount of data drawing and displaying is reduced, and the image display speed is improved. In the field of image matching, the global search is carried out by using the original data, which is undoubtedly time-consuming and labor-consuming, and the pyramid-based image matching algorithm can realize the step-by-step matching from coarse to fine, so that the operation time can be saved, and the matching precision can be improved.
And step S120, performing step-by-step matching on the image pyramid based on a preset search radius, and determining corresponding pixels in the stereo image pair and the reference image.
Step S130, carrying out space forward intersection processing on the pixel points with the same name to obtain object coordinates corresponding to the stereo pair.
And step S140, determining precision data among the stereo satellite images based on the object space coordinates, and performing precision quality inspection based on the precision data.
According to the method for detecting the precision quality of the stereoscopic satellite image, on the basis of automatically matching the connection points, free net adjustment is added to automatically eliminate wrong connection points, and meanwhile, multi-degree control points are introduced to synchronously detect absolute precision.
For convenience of understanding, the method for precision quality inspection of stereoscopic satellite images provided in the embodiments of the present application is described in detail below.
In an alternative embodiment, the image pyramid includes image data with at least two levels of resolutions, and for convenience of description, fig. 2 shows a schematic diagram of a two-level image pyramid, where sampling rates corresponding to each level are different, and resolutions of corresponding images in each level are different. By setting the image pyramids with different resolutions, the data with the specified resolution can be used by the retrieval pyramid, so that the operation amount of data drawing and displaying is reduced, and the image display speed is improved. The pyramid-based image matching algorithm can realize gradual matching from coarse to fine, so that the operation time can be saved, and the matching precision can be improved.
In the step S120, the image pyramid is subjected to step-by-step matching based on the preset search radius, and the corresponding pixel point of the stereoscopic image pair corresponding to the reference image is determined, which may include the following steps 1 to 3:
and 3, performing step-by-step matching in the image pyramid according to the position relation between the stereo image pair and the reference image and a preset search radius, and determining the homonymous pixel points corresponding to the reference image in the stereo image pair.
Firstly, extracting characteristic points from the whole image, and searching corresponding homonymous pixel points on the reference image by selecting the point position with the maximum gray level change (gradient) in the local window as the characteristic points.
The matching algorithm takes each feature point as a center, defines a certain template size to read an image data block to be matched, judges the position of the feature point in a reference image according to the initial position relation with the reference image, sets a certain search radius to read the reference image data block, wherein the search radius is larger than the template size so as to allow an original image block to slide in a window in the range of the reference image block and calculate a correlation coefficient.
Referring to fig. 3, a searched g image is traversed on a template f, and a pixel with the maximum correlation coefficient is searched by utilizing correlation comparison, so that the larger the searched image is, the slower the matching speed is; the smaller the template, the faster the matching speed, which affects the size of the template and the size of the search window. Generally, the reliability of matching is enhanced with the increase of the search window, however, an excessively large search window may result in an abnormally low algorithm operation efficiency, and in the case of a too small search window, a mismatch may occur if the region to be matched has no corresponding feature information. The window size has a large impact on the matching success rate. The size of the template can be basically determined according to empirical values, and the size of the search window is difficult to find out a universal and appropriate size due to different image conditions.
In one embodiment, the step 3 may further include a step 3.1 to a step 3.3:
step 3.1, determining a search area in the reference image according to the position relation between the stereo pair and the reference image;
step 3.2, performing window sliding in the image pyramid based on a preset search radius in the search area, performing step-by-step matching in the sliding process, and calculating correlation coefficients of the feature points to be matched and the matched target connection points; the size of the preset matching template is smaller than that of the preset searching radius;
and 3.3, determining the homonymous pixel points corresponding to the reference image in the stereoscopic image pair based on the correlation coefficient.
In an optional embodiment, step 3.2.1 to step 3.2.3 may be further included with respect to step 3.2:
step 3.2.1, performing window sliding on a preset initial layer of the image pyramid in the search area based on a preset search radius;
step 3.2.2, when the window slides, if the target connection point is matched, matching search is carried out on the next layer of the preset initial layer based on the position of the target connection point; if the target connection point is not matched, increasing the value of the preset search radius, performing matching search in a preset initial layer through the increased search radius, and performing matching search in a layer below the preset initial layer based on the position of the target connection point after the target connection point is matched; the resolution of the next layer of the preset initial layer is greater than that of the preset initial layer;
and 3.2.3, performing step-by-step circular matching search on the image pyramid until the image pyramid is circulated to the end layer of the image pyramid, and calculating the correlation coefficient between the feature point to be matched and the target connection point matched in the end layer.
The radius of the search window is dynamically changed in the step-by-step pyramid image matching process, and the optimal configuration of matching success rate and efficiency can be achieved. The matching efficiency can be accelerated by aiming at the matching of ideal undistorted images, and the matching success rate can be improved by aiming at the matching of nonlinear distorted images, so that the point location distribution is more uniform.
The main measure used for automatic matching is the correlation coefficient. The correlation coefficient matching method uses a correlation coefficient (normalized covariance) as a similarity measure. In statistics, the correlation coefficient is used to represent the correlation between two random variables, and extended to image matching, it can be used to represent the similarity between two images of the same size.
Wherein,
relative coefficient, called two images>
、
Is the mean value of the gray levels of the two images,
、
is the variance of two images>
The mean value of the two images after the corresponding points are multiplied. The correlation coefficient has the following properties:
①
；
②
；
③
is that images X and Y are linearly related by 1.
It can be seen that the correlation coefficient
For representing the similarity degree of the linear relation between the images X and Y, the closer the correlation coefficient is to 1 or-1, the more obvious the linear similarity degree between the images is.
Furthermore, considering that the matching result of the connection points is sometimes matched to wrong points due to poor texture quality or overlarge search window, in order to enable the accuracy of the connection points in the area to be integrally optimal, and simultaneously, automatically eliminating the connection points with the errors exceeding the limit, free net adjustment is needed. Therefore, in an embodiment, when step-by-step matching search is performed, the matched target connection point is processed based on the block level-difference model, so as to obtain a residual vector corresponding to the target connection point after level difference; and determining an error point in the target connection point based on the residual vector and a preset residual threshold value, and eliminating the error point.
In one embodiment, the adjustment algorithm model may adopt an image space correction-based RFM model, the imaging field angle of the optical satellite image is small, the light of each pixel is close to parallel imaging, and the geometric error in the monoscopic image product is mainly low-order linear error in the image space, so that the compensation error adopts a first-order affine transformation model, and the formula is as follows:
in the formula
、
For image-space translation of the orientation parameter, <' >>
For two-dimensional affine transformation parameters>
For corrected image space coordinates>
、
Is the object coordinates of the connection point. The above formula synthesizes the RFM model to obtain the basic mathematical model of the block adjustment, and the formula is as follows:
6 parameters of the affine transformation model and the image side correction number of the connecting points can be obtained by listing the error equations and carrying out error calculation.
And (4) after the error is eliminated, the residual vectors of each connecting point have good consistency in size and direction, 2 times of errors are selected as a residual threshold value during error elimination, and the connecting points with the errors larger than 2 times are considered as error points. After removing the error points, the error correction is carried out again until no point location is removed or the condition of reaching the maximum iteration times is cut off, and the method can effectively inhibit the influence of the matching error points on the error correction result and the quality inspection precision.
In an optional embodiment, the stereo pair in the same measurement area of the stereo satellite image includes a first image and a second image; the homonymous pixel point comprises a first connecting point located on the first image and a second connecting point located on the second image, and the first connecting point and the second connecting point are homonymous points. For example, a first image and a second image included in a stereo pair in the same measurement area of the stereo satellite image are respectively a front view image and a rear view image, and the homonymous pixel points are corresponding to homonymous pixel points on the reference image respectively.
In one embodiment, the method for performing spatial forward rendezvous processing on pixels with the same name to obtain object coordinates corresponding to a stereopair includes:
determining a ground image point where the pixels with the same name meet the ground based on the coordinates of the first connection point and the coordinates of the second connection point;
and calculating based on the ground image points and the rational function model, and determining the object space coordinates corresponding to the stereopair.
In one embodiment, the purpose of the spatial forward intersection is to solve the object coordinates by listing 4 equations with the RPC model (rational function model) by the coordinates of the image points of the same name points (connection points) of the left and right photographs (equation:)
、
、
). Since the satellite manufacturer avoids revealing relevant parameters of the satellite, the source data only provides RPC parameters, and therefore the RPC model is used in the forward intersection of the space.
The RPC parameters are calculated and fitted at the object-side virtual control points based on a rigorous imaging model, which describes the interrelation between the image point coordinates and the object-side coordinates, and the model has 90 parameters, which are defined as follows:
wherein
、
、
、
Are polynomials of the form, for example:
where (U, V, W) is the normalized ground coordinates and (r, c) is the normalized pixel coordinates:
in the formula (A), (B)
,
,
,
,
) For normalizing the translation parameter, ("based on>
,
,
,
,
) For normalizing the ratio parameter, they are combined with>
~
、
~
、
~
、
~
A total of 90 parameters are stored in the rpc file.
During the frontal intersection, the coordinates of the frontal image points (
、
) Sit with the back vision image pointStandard (` whether or not `)>
、
) Co-crossing at a ground point (` H `)>
、
、
) Thus, 4 equations (3 unknowns) can be listed, and the ground point (@ based) can be solved iteratively after linearization>
、
、
)。
In the invention, 2 groups of stereopairs are input, four-degree overlapping can be generated in the overlapping area, 2 object space coordinates can be calculated after front intersection processing (
、
、
) The difference between the two is considered as the relative accuracy between the three-dimensional models.
Further, when the precision quality inspection is performed based on the precision data, the precision quality inspection can be performed based on multiple control points and/or error evaluation parameters; the multi-degree control points are homonymous image points obtained by importing field control points in the stereo image pair or matching the field control points with a standard image superposition digital elevation model.
The control points reflect the absolute orientation accuracy of the three-dimensional model, and the introduction of the multi-degree control points is the key for checking the absolute accuracy of the three-dimensional model. The multi-degree control point is a homonymous image point which is imported from a field control point in a front-view and rear-view stereoscopic image pair or is automatically matched with a reference image and a DEM (digital elevation model), and the error between the point and an actual elevation value is regarded as the absolute accuracy of the stereoscopic model through front intersection processing. If the multi-degree control points are positioned at the position of the stereo image butt joint edge, the multi-degree control points are positioned in an N-degree overlapping area, at the moment, the relative precision can be checked through the multi-degree control points, the absolute precision can be checked, and the comprehensive consideration of the precision check of the stereo model is realized.
When the precision quality inspection is carried out based on the error evaluation parameters, the parameters commonly used for the error precision evaluation are as follows: medium error, root mean square error, etc. Taking the median error as an example, the absolute accuracy error in the invention is as follows:
wherein
The difference value between the elevation value of the intersection in front of a certain control point and the known elevation value (true value) of the control point is as follows:
the relative accuracy error is:
wherein
Elevation values for a preceding encounter of stereo pair 1, in which>
Elevation values for the frontal encounter of the stereo pair 2.
Fig. 4 shows an effect diagram of quality inspection performed by the method of the present application, a set of GF7 data is input, and as shown in table 1, it takes 31 seconds for a total of 27 connection points to be matched in a 4-degree overlap region in an experiment, 35 control points are imported, and it takes 30 minutes for manual point location adjustment. The relative precision error of the elevation Z of the connecting point is 0.046 m, the absolute precision error of the elevation Z of the control point is 0.420 m, and each point position is checked to be correct and reliable manually. Through tests, the method provided by the invention can effectively perform relative and absolute precision quality inspection on the three-dimensional model.
TABLE 1 results of precision quality inspection
In summary, the method provided by the embodiment of the application can realize the rapid quality inspection of the absolute relative precision of the stereo model of the original image adjustment result, the trouble of manual thorn transferring connection points is eliminated, the precision of the matching points is improved by the adjustment of the free network, and the synchronous quality inspection of the absolute and relative precision is realized by the multi-degree control points.
Based on the above method embodiment, the embodiment of the present application further provides a device for precision quality inspection of stereoscopic satellite images, as shown in fig. 5, the device mainly includes the following components:
an image pyramid construction module 510, configured to obtain a stereo pair in the same measurement area of a stereo satellite image, and construct an image pyramid corresponding to the stereo pair;
a step-by-step matching module 520, configured to perform step-by-step matching on the image pyramid based on a preset search radius, and determine a same-name pixel point in the stereoscopic image pair corresponding to the reference image;
a front intersection processing module 530, configured to perform spatial front intersection processing on the pixels with the same name to obtain object coordinates corresponding to the stereo pair;
and the precision quality inspection module 540 is configured to determine precision data between the stereo satellite images based on the object coordinates, and perform precision quality inspection based on the precision data.
The device of three-dimensional satellite image precision quality inspection that this application embodiment provided can realize the quick three-dimensional model absolute relative precision quality inspection of original image adjustment result, has saved the trouble of artifical commentaries on classics thorn tie point, and the adjustment of free network has improved the precision of matching point simultaneously, and the synchronous quality inspection of absolute and relative precision has been realized to many degrees control points.
In a possible implementation, the progressive matching module 520 is further configured to:
extracting the maximum gray gradient point position in a local window from the stereo image pair, and determining the maximum gray gradient point position as a feature point to be matched;
taking the characteristic points to be matched as a center, and reading image data blocks to be matched based on a preset matching template;
and matching step by step in the image pyramid according to the position relation between the stereoscopic image pair and the reference image and a preset search radius, and determining the homonymous pixel points corresponding to the stereoscopic image pair and the reference image.
In a possible implementation, the progressive matching module 520 is further configured to:
determining a search area in the reference image according to the position relation between the stereo pair and the reference image;
performing window sliding on the image pyramid in the search area based on a preset search radius, performing step-by-step matching in the sliding process, and calculating a correlation coefficient between the feature point to be matched and the matched target connection point; the size of the preset matching template is smaller than that of the preset search radius;
and determining the homonymous pixel points corresponding to the reference image in the stereoscopic image pair based on the correlation coefficient.
In a possible implementation, the progressive matching module 520 is further configured to:
performing window sliding on a preset initial layer of the image pyramid in the search area based on a preset search radius;
when the window slides, if the target connection point is matched, performing matching search on the next layer of a preset initial layer based on the position of the target connection point; if the target connection point is not matched, increasing the value of the preset search radius, performing matching search on a preset initial layer through the increased search radius, and performing matching search on the next layer of the preset initial layer based on the position of the target connection point after the target connection point is matched; the resolution of the next layer of the preset initial layer is greater than that of the preset initial layer;
and performing step-by-step circular matching search on the image pyramid until the image pyramid is circulated to the end layer of the image pyramid, and calculating the correlation coefficient between the feature point to be matched and the target connection point matched in the end layer.
In a possible implementation, the apparatus further includes an error elimination module, configured to:
when step-by-step matching search is carried out, the matched target connection point is processed based on the block level difference model, and a residual vector corresponding to the target connection point after adjustment is obtained;
and determining an error point in the target connection point based on the residual vector and a preset residual threshold, and removing the error point.
In one possible embodiment, a stereo pair in the same measurement area of the stereo satellite image comprises a first image and a second image; the homonymous pixel point comprises a first connecting point positioned in the first image and a second connecting point positioned in the second image, and the first connecting point and the second connecting point are homonymous points;
the front-meeting processing module 530 is further configured to:
determining a ground image point of the same-name pixel point intersected on the ground based on the coordinates of the first connecting point and the coordinates of the second connecting point;
and calculating based on the ground image points and the rational function model, and determining the object coordinates corresponding to the stereopair.
In a possible embodiment, the precision quality inspection module 540 is further configured to:
performing precision quality inspection based on the multi-degree control points and/or the error evaluation parameters; and the multi-degree control points are homonymous image points obtained by importing the field control points in the stereo image pair or matching the field control points with a standard image superposition digital elevation model.
The implementation principle and the generated technical effects of the device for quality inspection of stereoscopic satellite images provided by the embodiment of the present application are the same as those of the method embodiment described above, and for brief description, reference may be made to the corresponding contents in the method embodiment for quality inspection of stereoscopic satellite images.
An electronic device is further provided in an embodiment of the present application, as shown in fig. 6, which is a schematic structural diagram of the electronic device, where the electronic device 100 includes a processor 61 and a memory 60, the memory 60 stores computer-executable instructions capable of being executed by the processor 61, and the processor 61 executes the computer-executable instructions to implement any one of the above methods for precision quality inspection of stereoscopic satellite images.
In the embodiment shown in fig. 6, the electronic device further comprises a bus 62 and a communication interface 63, wherein the processor 61, the communication interface 63 and the memory 60 are connected by the bus 62.
The Memory 60 may include a high-speed Random Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least one disk Memory. The communication connection between the network element of the system and at least one other network element is realized through at least one communication interface 63 (which may be wired or wireless), and the internet, a wide area network, a local network, a metropolitan area network, and the like can be used. The bus 62 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus 62 may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 6, but this does not indicate only one bus or one type of bus.
The processor 61 may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware or instructions in the form of software in the processor 61. The Processor 61 may be a general-purpose Processor, and includes a Central Processing Unit (CPU), a Network Processor (NP), and the like; the device can also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, or a discrete hardware component. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in the memory, and the processor 61 reads information in the memory, and completes the steps of the method for precision quality inspection of stereoscopic satellite images according to the foregoing embodiment in combination with hardware thereof.
The embodiment of the present application further provides a computer-readable storage medium, where computer-executable instructions are stored, and when the computer-executable instructions are called and executed by a processor, the computer-executable instructions cause the processor to implement the method for performing precision quality inspection on stereoscopic satellite images, and specific implementation may refer to the foregoing method embodiment, and is not described herein again.
The method and the apparatus for precision quality inspection of stereoscopic satellite images and the computer program product of the electronic device provided in the embodiments of the present application include a computer-readable storage medium storing program codes, where instructions included in the program codes may be used to execute the methods described in the foregoing method embodiments, and specific implementations may refer to the method embodiments and are not described herein again.
Unless specifically stated otherwise, the relative steps, numerical expressions, and values of the components and steps set forth in these embodiments do not limit the scope of the present application.
The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings or orientations or positional relationships that the products of the present invention are conventionally placed in use, and are used only for convenience in describing the present application and simplifying the description, but do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present application. Furthermore, the terms "first," "second," and the like are used merely to distinguish one description from another, and are not to be construed as indicating or implying relative importance.
In the description of the present application, it is further noted that, unless expressly stated or limited otherwise, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meaning of the above terms in this application will be understood to be a specific case for those of ordinary skill in the art.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. A method for precision quality inspection of stereoscopic satellite images is characterized by comprising the following steps:
acquiring a stereopair in the same measurement area of the stereoscopic satellite image, and constructing an image pyramid corresponding to the stereopair;
step-by-step matching is carried out on the image pyramid based on a preset search radius, and homonymous pixel points corresponding to the reference image in the stereoscopic image pair are determined;
carrying out space forward intersection processing on the homonymous pixel points to obtain object space coordinates corresponding to the stereopair;
and determining precision data among the stereo satellite images based on the object space coordinates, and performing precision quality inspection based on the precision data.
2. The method according to claim 1, wherein the image pyramid comprises at least two levels of resolution image data; matching the image pyramid step by step based on a preset search radius, and determining the homonymous pixel points corresponding to the reference image in the stereoscopic image pair, wherein the method comprises the following steps:
extracting the maximum gray gradient point position in a local window from the stereo image pair, and determining the maximum gray gradient point position as a feature point to be matched;
taking the characteristic points to be matched as a center, and reading image data blocks to be matched based on a preset matching template;
and step-by-step matching is carried out in the image pyramid according to the position relation between the stereo image pair and the reference image and a preset searching radius, and homonymous pixel points corresponding to the stereo image pair and the reference image are determined.
3. The method of claim 2, wherein the step-by-step matching is performed in the image pyramid according to the position relationship between the stereo image pair and the reference image and a preset search radius, and the determination of the pixel points with the same name in the stereo image pair corresponding to the reference image comprises:
determining a search area in the reference image according to the position relation between the stereo pair and the reference image;
performing window sliding on the image pyramid in the search area based on a preset search radius, performing step-by-step matching in the sliding process, and calculating a correlation coefficient between the feature point to be matched and the matched target connection point; the size of the preset matching template is smaller than that of the preset search radius;
and determining the homonymous pixel points corresponding to the reference image in the stereoscopic image pair based on the correlation coefficient.
4. The method for precision quality inspection of stereoscopic satellite images according to claim 3, wherein the window sliding is performed in the image pyramid based on a preset search radius in the search area, the step-by-step matching is performed in the sliding process, and the correlation coefficient between the feature point to be matched and the matched target connection point is calculated, and the method comprises:
performing window sliding on a preset initial layer of the image pyramid in the search area based on a preset search radius;
when the window slides, if the target connection point is matched, performing matching search on the next layer of a preset initial layer based on the position of the target connection point; if the target connection point is not matched, increasing the value of the preset search radius, performing matching search on a preset initial layer through the increased search radius, and performing matching search on the next layer of the preset initial layer based on the position of the target connection point after the target connection point is matched; the resolution of the next layer of the preset initial layer is greater than that of the preset initial layer;
and performing step-by-step circular matching search on the image pyramid until the image pyramid is circulated to the end layer of the image pyramid, and calculating the correlation coefficient between the feature point to be matched and the target connection point matched in the end layer.
5. The method for precision quality inspection of stereoscopic satellite imagery according to claim 4, wherein the method further comprises:
when step-by-step matching search is carried out, the matched target connection point is processed based on the block level difference model, and a residual vector corresponding to the target connection point after adjustment is obtained;
and determining an error point in the target connection point based on the residual vector and a preset residual threshold value, and eliminating the error point.
6. The method for precision quality inspection of stereoscopic satellite images according to claim 1, wherein the stereoscopic image pair in the same inspection area of the stereoscopic satellite image comprises a first image and a second image; the homonymous pixel point comprises a first connecting point positioned in the first image and a second connecting point positioned in the second image, and the first connecting point and the second connecting point are homonymous points;
carrying out space forward intersection processing on the homonymous pixel points to obtain object space coordinates corresponding to the stereopair, and the method comprises the following steps:
determining a ground image point of the same-name pixel point intersected on the ground based on the coordinates of the first connecting point and the coordinates of the second connecting point;
and calculating based on the ground image points and a rational function model, and determining object coordinates corresponding to the stereopair.
7. The method of claim 6, wherein the performing the precision quality inspection based on the precision data comprises:
performing precision quality inspection based on the multi-degree control points and/or the error evaluation parameters; and the multi-degree control points are homonymous image points obtained by importing the field control points in the stereo image pair or matching the field control points with a standard image superposition digital elevation model.
8. A device for precision quality inspection of stereoscopic satellite images is characterized by comprising:
the image pyramid construction module is used for acquiring a stereopair in the same measurement area of the stereoscopic satellite image and constructing an image pyramid corresponding to the stereopair;
the step-by-step matching module is used for performing step-by-step matching on the image pyramid based on a preset search radius and determining homonymous pixel points corresponding to the reference image in the stereoscopic image pair;
the front intersection processing module is used for carrying out space front intersection processing on the pixel points with the same name to obtain object space coordinates corresponding to the stereo pair;
and the precision quality inspection module is used for determining precision data among the stereo satellite images based on the object space coordinates and performing precision quality inspection based on the precision data.
9. An electronic device, comprising a processor and a memory, wherein the memory stores computer-executable instructions executable by the processor, and the processor executes the computer-executable instructions to implement the method for precision quality inspection of stereoscopic satellite images according to any one of claims 1 to 7.
10. A computer-readable storage medium storing computer-executable instructions which, when invoked and executed by a processor, cause the processor to implement the method for performing the stereoscopic satellite image precision quality inspection according to any one of claims 1 to 7.
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